Patent data analytics is an invaluable tool for navigating patent prosecution as effectively and efficiently as possible, but it is important to remember that the data sets that will be most useful to you as a patent professional will change throughout the various stages of the patent process, from pre-filing to making after-final decisions. Utilizing good data to inform your decisions can have a tremendous impact on your application’s performance, however, not all data is good data.

Common Types of Bad Data

Outdated Data

Outdated patent data is not predictive patent data. While a patent examiner’s or an art unit’s historical patent data is a useful guidepost for predicting the future actions of the patent examiner or art unit, patent professionals should remain cognizant that new trends emerge over time. For example, an assessment of a patent examiner based on the patent examiner’s entire career statistics may create an inaccurate depiction of the patent examiner in the present. As patent examiners gain experience and confidence, their decisions change as well. To avoid relying on outdated information, remember to pay attention to more recent trends before using patent data to make patent prosecution decisions. Advanced patent metrics, such as the LexisNexis Examiner Lottery Framework™ available on the LexisNexis PatentAdvisor® platform, take into account several data sources and point you in the direction of the most current data trends.

Missing Data

Decisions made with partial information are usually less effective than decisions based on the full picture. When tackling large projects, such as assessing your law firm’s patent prosecution performance or the overall performance of a large corporation’s patent portfolio, simply ensuring that you have all of the applicable patent documents at your disposal can be a challenge, but It is important to gather all relevant information before an assessment. PatentAdvisor’s patent portfolio management tools make it easy to quickly find law firm and assignee patent data and then save that data in an electronic portfolio for statistical analytics. Aggregating patent documents is no longer necessary – PatentAdvisor has that part covered.

Data Sliced the Wrong Way

The patent prosecution strategy you develop will depend on the information you choose to consider beforehand, but to earn the best possible outcome, it is imperative that you choose the best data set for the situation.  High-level patent statistics pertaining to the USPTO as a whole or to a specific group art unit can be useful for making generalizations or for determining group trends, but there may be situations when your patent examiner does not conform to group statistics.  With PatentAdvisor, users can filter data sets from high-level down to examiner-specific information in as little as a few clicks.


Data without Accounting for an Important Variable

It is easy to draw conclusions from a patent statistic without considering the surrounding circumstances. For example, you may conclude that a patent examiner is unlikely to allow your patent because her historical patent statics show a low career allowance rate. What you may not realize is that the patent examiner is fairly new to the USPTO, and rejected many of the first patent applications she reviewed due to a lack of confidence in her own ability to evaluate effectively. More recently, however, she has gained confidence and is much more likely to allow a patent to issue. PatentAdvisor’s proprietary algorithms pick up on the variables you might have overlooked, and it produces more reliable metrics so you can make better decisions. PatentAdvisor’s advanced metrics take into account the big picture so that users never miss a beat.



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审查员检索:允许您按审查员的名字检索专利分析的可过滤的、审查员特定的仪表板,包括拒绝特定的统计数据、上诉统计数据、审查统计数据、面谈统计数据、RCE 积压和时间表。

通过提供目前可获取的最强大的申请详细资料,包括审查员时间表、审查员授予率和审查意见通过的平均时间和数量,QuickPair 轻松取代了美国专利商标局公共 PAIR 系统。

PatentAdvisor 是首款数据驱动型专利策略工具,为制定有效的审查策略提供了系统的方法。了解某些专利申请为何比其他申请需要更长的时间才能获得核准,然后利用这些知识来设计更好的专利审查策略。


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